1. Field of the Invention
Embodiments of the invention relate generally to the processing of image data. More particularly, an embodiment of the invention calculates probability information for use in determining a color correction for image data.
2. Background Art
Unlike human vision, imaging devices such as digital cameras can not adapt their spectral responses to cope with different lighting conditions. The original appearance of a scene captured by an imaging device under a particular illumination can be recovered by transforming output of the imaging device—e.g. image information represented in a red/green/blue (RGB) color space or in a luma/blue chroma/red chroma (YCbCr) color space. Such transformations typically use chromatic adaptation models, and are the basis of several existing color balancing methods. These models provide a transformation from tristimulus values in one viewing condition into tristimulus values corresponding to a second viewing condition. Existing chromatic adaptation models vary in how the particular values of transformation coefficients are obtained, but they are typically based on the Von Kries hypothesis, which states that chromatic adaptation is an independent gain regulation of the three large, medium and small (or LMS) cone signals through three different gain coefficients. In these models the RGB channels are usually considered as an approximation of the LMS retinal wavebands, so that the post-adaptation RGB values can be obtained with a Von Kries diagonal transform utilizing three gains only. However, this type of modeling may not hold true for a given imaging device.
Often, an imaging device will have for each color channel (e.g. red, green, blue) its own characteristic spectral response across a range of the light spectrum, e.g. a response which does not sufficiently conform to assumptions made for a given chromatic adaptation model. Furthermore, when such an imaging device captures an image of a target under a particular viewing condition, often there is inadequate information about the particular viewing condition for use in image processing. The anomalous spectral responses of imaging devices and the limited availability of information about viewing conditions under which images are captured may limit the effectiveness of existing methods of image processing such as color correction.